strands-agents / evals

What it does

• Multiple Evaluation Types. Output evaluation, trajectory analysis, tool usage assessment, and interaction evaluation
• Multimodal Evaluation. MLLM-as-a-Judge evaluators for image-to-text tasks with built-in rubrics
• Skill Evaluation. Assess which skills a skill-equipped agent selected and whether it followed their instructions
• Dynamic Simulators. Multi-turn conversation simulation with realistic user behavior, goal-oriented interactions, and LLM-powered tool simulation with shared state
• LLM-as-a-Judge. Built-in evaluators using language models for sophisticated assessment with structured scoring